ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective To compare the performance of 7 Chinese-developed GenAI models (DeepSeek, Wenxin Yiyan, Tongyi, Doubao, Kimi, Hunyuan, and iFLYTEK Spark) in responding to common diseases of the pediatric genitourinary system and to explore their potential applications.Methods A total of 80 questions covering basic disease information, diagnosis, treatment, and prognosis related to “hypospadias, hydronephrosis, and cryptorchidism” were developed as prompts.The models were tested under 3 modes:“quick thinking, ”“deep thinking, ” and “deep thinking + internet access.” The results were evaluated in a blinded review by two pediatric urologists.The responses were graded into 4 levels—A, B, C, and D—based on accuracy, completeness, and relevance.The proportions of responses rated as A and A+B were statistically analyzed and compared across the different models/modes.Results The “deep thinking” mode of DeepSeek demonstrated the best performance, with 88% of responses rated as A and 96% rated as A+B.DeepSeek (deep thinking + internet access), Doubao (quick thinking), Hunyuan (deep thinking), and Doubao (deep thinking + internet access) followed closely, also showing excellent response capabilities.Among the top 5 models/modes, significant differences were observed in the proportion of Alevel responses (P＜0.05), while differences in the proportion of A+B-level responses were not statistically significant (P＞0.05).Conclusion Certain Chinese-developed GenAI models, represented by DeepSeek (deep thinking), demonstrate significant application potential.However, they still cannot consistently provide recommendations rated at the A+B level (recommended grade or higher) with 100% accuracy.In clinical practice, both doctors and patients should view GenAI as an auxiliary tool for education and information acquisition rather than as a final decision-making authority.All information must be reviewed and confirmed by professional physicians.

Objective To investigate the value of fractional-order calculus(FROC)and continuous-time random-walk(CTRW)diffusion models based on readout segmentation of long variable echo-trains(RESOLVE)in identifying benign and malignant lesions in the head and neck.Methods A retrospective analysis was conducted on 61 patients pathologically confirmed head and neck lesions,including 19 benign lesions(BL)and 42 malignant lesions(ML).The ML were further divided into a lymphoma subgroup(LS)with 9 cases(14 lesions)and a non-lymphoma malignant lesion subgroup(MLS)with 33 cases.The parameters of DFROC,βFROC,μFROC,DCTRW,αCTRW and βCTRW were obtained from the two diffusion models;Independent sample t-tests or U tests were used to compare the differences in each parameter between benign and malignant groups and among various subgroups,and the receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of each parameter.Area under the curve(AUC)was compared by DeLong test.Results DFROC,μFROC,DCTRW and αCTRW showed significant differences between benign and malignant,BL and LS,BL and MLS and LS and MLS,with αCTRW showed the highest diagnostic efficacy;βFROC showed differences between BL and LS,BL and MLS,whileβCTRW did not show differences between benign and malignant groups,and among subgroups.Conclusion FROC and CTRW diffusion models based on RESOLVE can distinguish between benign and malignant head and neck lesions with multiple parameters,and provide metrics reflecting tissue heterogeneity.

Objective:To detect the serum levels of 25(OH)D,miR-125b-5p,hypoxia-inducible factor-1α(HIF-1α)and vascular endothelial growth factor A(VEGFA)in patients with multiple myeloma(MM),and explore the role of miR-125b-5p/HIF-1α pathway in the involvement of vitamin D deficiency in the pathogenesis of MM.Methods:Fifty three newly diagnosed/relapsed MM patients admitted to the department of hematology of our hospital from October 2021 to December 2023 were included.Meanwhile,25 healthy individuals matched in gender and age from our hospital's Health Management Center were selected as controls.The serum level of 25(OH)D was monitored by mass spectrometry,the serum level of miR-125b-5p was detected by real-time fluorescence quantitative PCR,and serum levels of HIF-1α and VEGFA were measured by enzyme-linked immunosorbent assay.The levels of 25(OH)D,miR-125b-5p,HIF-1α,and VEGFA were compared between the two groups.According to the level of 25(OH)D,the MM patients were divided into vitamin D deficiency group(＜20 ng/ml)and vitamin D non-deficiency group(≥ 20 ng/ml),and the levels of miR-125b-5p,HIF-1α,and VEGFA were compared between the two groups.The correlations between 25(OH)D,miR-125b-5p,HIF-1α and VEGFA were analyzed.The receiver operating characteristic(ROC)curve analysis was used to determine the diagnostic value of25(OH)D combined with miR-125b-5p for newly diagnosed MM.Results:The level of 25(OH)D in MM patients was significantly lower than that in control group(P＜0.01).There was no significant difference in 25(OH)D level between newly diagnosed and relapsed MM patients(P＞0.05).Compared with the control group,the level of miR-125b-5p was significantly reduced in MM patients(P＜0.01),while the levels of HIF-1α and VEGFA were significantly increased(both P＜0.001).In MM patients,the miR-125b-5p level in the vitamin D deficiency group was significantly decreased than that in the non-deficiency group(P＜0.01),while the levels of HIF-1 α and VEGFA were significantly increased(both P＜0.05).In MM patients,25(OH)D was positively correlated with miR-125b-5p,while negatively correlated with HIF-1α and VEGFA(both P＜0.05).Moreover,miR-125b-5p was negatively correlated with HIF-1α and VEGFA(both P＜0.05).The area under the curve(AUC)for diagnosing MM with 25(OH)D,miR-125b-5p,and their combination were 0.699,0.751,and 0.791,respectively.Conclusion:The incidence of vitamin D deficiency is high in MM patients.Vitamin D deficiency may promote angiogenesis and participate in the occurrence and development of MM by downregulating miR-125b-5p and upregulating HIF-1α and VEGFA expression.

Objective:To investigate the value of carotid，radial and podalic artery intima thickness（CIT，RIT，PIT）combined with monocyte to high-density lipoprotein ratio（MHR）in predicting the severity of coronary artery stenosis in patients with premature coronary artery disease（PCAD）.Methods:A total of 80 patients with PCAD who received treatment in Henan Provincial People's Hospital from October 2023 to May 2024 were prospectively recruited，and they were divided into high group（≥41 score，40 cases）and low group（＜41 score，40 cases）according to the median dichotomy of Gensini score. Thirty-four gender，age and body mass index（BMI）-matched healthy volunteers were selected as the control group. The CIT，RIT，PIT，media and intima media thickness of carotid，radial artery and podalic artery（CMT，RMT，PMT，CIMT，RIMT，PIMT）were measured using 24 MHz ultra-high frequency ultrasound probe，and the ratio of intima to media thickness（CIT/CMT，RIT/RMT，PIT/PMT）was calculated. The differences of general clinical data，laboratory indexes and ultrasonic parameters among the three groups were compared. Risk factors affecting the severity of coronary stenosis in PCAD patients were explored by binary logistic regression. Subject working characteristic curves were plotted，area under the curve（AUC）was calculated，and the values of each ultrasound parameter and MHR in the independent and combined diagnosis of the severity of coronary artery stenosis in PCAD patients were evaluated.Results:①There were no statistically significant differences in age，gender，BMI，total cholesterol，CMT，RMT and PMT among the three groups（all P＞0.05）. There were no statistically significant differences in the comparison of smoking，hypertension，diabetes mellitus，systolic blood pressure，diastolic blood pressure，low-density lipoprotein cholesterol，total cholesterol，and triglycerides between the two subgroups of the PCAD（all P>0.05）. ②CIT，CIMT，CIT/CMT，RIT，RIMT，RIT/RMT，PIT，PIMT，PIT/PMT were thickened in the high group compared with the low group，and MHR was higher than in the low group（all P<0.05），the differences in the above parameters remained statistically significant when comparing the PCAD group with the control group（all P<0.05）. ③The AUC values for MHR，CIT，RIT and PIT alone to predict the severity of coronary stenosis in patients with PCAD were 0.781，0.767，0.780 and 0.722，respectively. The combined diagnostic efficiency of the four parameters was better than the independent diagnostic efficiency（AUC = 0.885）. Conclusions:CIT，RIT and PIT are thicker in PCAD patients with high Gensini score and the combination of artery intima thickness and MHR has good efficacy in predicting the severity of coronary artery stenosis in PCAD patients.

Objective:To evaluate the changes of carotid intima thickness（CIT）and stiffness parameters in ankylosing spondylitis（AS）patients by 24 MHz ultra-high frequency ultrasound probe and RF-data based quantitative analysis on vessel stiffness（R-VQS），and to explore its influencing factors.Methods:Sixty patients with AS who underwent consultation at Henan Provincial People's Hospital from November 2023 to May 2024 were prospectively collected as AS group，54 healthy volunteers matched for sex，age，and body mass index were collected as control group. CIT were measured using a 24 MHz ultra-high frequency ultrasound probe，hardness coefficien（HC）and pulse wave velocity（PWV）were measured by R-VQS，the differences of the parameters between the two groups were compared. The changes of carotid artery elasticity and intima thickness and their influencing factors in patients with AS were explored by univariate and multivariate linear regression analysis.Results:①C-reactiveprotein，erythrocyte sedimentation rate（ESR），neutrophil count and neutrophil to lymphocyte ratio（NLR）were elevated in the AS group compared with the control group，and the differences were statistically significant（all P < 0.05）. ②CIT，carotid intima-media thickness（CIMT），HC，PWV and epicardial adipose tissue thickness（EATT）were all increased in the AS group compared with the control group，and the differences were statistically significant（all P < 0.05）. ③Multifactorial linear regression analysis showed that EATT，ESR were the main influencing factors of HC，PWV and CIT（ β=2.192，0.031；1.792，0.002；0.097，0.001；all P＜0.05）. Conclusions:Carotid CIT，CIMT，HC，PWV and EATT are all higher in the AS patients，and ESR and EATT are the main influencing factors of HC，PWV，and CIT，suggesting that more attention should be paid to the detection of ESR and EATT in patients with AS when interventions are performed clinically.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

The"capitation payment with retained surplus and shared accountability for reasonable overruns"mechanism constitutes a pivotal institutional framework for advancing the high-quality development of County Medical Communities(CMCs).This study addresses two critical operational challenges:identifying the sources of medical insurance fund surplus and optimizing the governance of fund retention processes.Grounded in transaction cost theory,we develop an analytical framework examining the formation of medical insurance fund surplus through the dual lenses of intra-organizational dynamics within CMCs and external medical insurance payment mechanism design.Utilizing Deqing County,Zhejiang Province as an empirical case,this research proposes a five-pronged strategy:Clarifying generation channels of insurance fund surplus,scientifically determining regional medical insurance budgets,implementing bundled payment mechanisms for CMCs,adopting hybrid payment models integrating unified and differentiated approaches,and establishing performance-based incentive systems.These findings elucidate the formative pathways of medical insurance fund surplus while offering theoretical and practical insights for enhancing payment system reforms to support CMC development.

Objective:To explore the coordinated development status of the medical service supply-economy-society trinity systems in Zhejiang Common Prosperity Demonstration Zone,and to offer references for formulating policies conducive to the efficient and coordinated development of these three systems.Methods:Based on the panel data from 2013 to 2022,this research was conducted on the 11 prefectural-level cities in Zhejiang Province.Firstly,an evaluation index system for the three systems was established,and the entropy method was employed to determine the weights of each index and calculate the comprehensive evaluation index.Secondly,a triangular model was introduced to delineate the relative relationships among the three systems,and the coupling coordination degree model was utilized to disclose the coordination degree of the three systems.Finally,the spatial autocorrelation analysis method was applied to investigate the spatial autocorrelation of the coupling coordination degree of the three systems.Results:(1)On the whole,the development status of the three systems has improved over time,yet the comprehensive development level remains to be improved.(2)Overall,each prefectural-level city has transited from a medical service supply-society-dominated development to a balanced and coordinated development of the medical service supply-economy-society trinity systems.The coupling coordination degree of the three systems has risen from 0.468(on the verge of imbalance)in 2013 to 0.609(primary coordination)in 2022,presenting an upward trend in general.However,the coordination level remains to be improved and there exist imbalances among regions.(3)The coupling coordination degree of the three systems in Zhejiang Province exhibits a significant positive spatial correlation,and the spatial distribution characteristics are relatively stable. Conclusion:The coupling coordination degree of the medical service supply-economy-society trinity systems in Zhejiang Province awaits further enhancement. At the level of Zhejiang Province,favorable policy support should be provided,the layout of medical resources should be rationally planned,and high-quality economic and social development should be promoted. Each prefectural-level city should formulate strategies for medical service supply,economic,and social development in accordance with its own development level and local conditions,strengthen inter-city linkage and cooperation,and thereby elevate the coordinated development level of the three systems.